At the end of every year, I take a few minutes to think back on the most disruptive technologies of the previous year and consider what tomorrow might have in store. This past year will undoubtedly be remembered as the year of Artificial Intelligence and chatbots. However, when it comes to developing technologies that truly change the way organizations operate, the hype of the simplistic call-and-response chatbots we saw this year will likely be just a small blip on a much longer journey towards true AI. As we approach 2019, I believe that technologies that will truly impact business operations and ROI may not garner as much hype but will bring greater change. This includes trends such as digital transformation, Deep Learning, and low-code/no-applications.

As we close out this year and wade knee-deep into 2019 planning, here are a few thoughts on where innovative technologies of the future will take us.

Augmented Analytics and Natural Language Processing

By the end of 2019, many finance and management teams will benefit from the automation that Machine Learning algorithms can bring when applied to massive datasets. They will no longer have to spend time on transactional tasks that don’t add value. Deep Learning algorithms will take advantage of relevant information and help put it into context, memorizing learnings and applying them to new inputs. Organizations will benefit from a multi-layer neural network that learns by example and improves the quality of its results over time. We’ll see an increase in use cases and applications in 2019.

Citizen developers represent a new generation in the workforce. They see technology as a way to create value in their work, opening doors to innovation and higher efficiency, and providing new ways of accomplishing goals. Tools are now emerging that allow them to quickly develop front-end applications that map exactly to the processes used by their organizations and their teams, taking advantage of business data and intelligence that was once relegated to the back office. Vendors are redesigning the software architectures to support this change, enabling customers to build out from the core using loosely coupled microservices so employees can create service-enhancing ERP extensions in their own image. The citizen developer market will be huge in the coming years, but this growth will be driven by citizen developers — not software vendors.

The End of Massive Software Customization Projects

Applications architectures are changing. Monolithic architectures are yielding to microservice architectures. Big monolithic software applications — the ones that still dominate many large enterprises — will be replaced by architectures far more flexible, distributed and scalable than older ones. Enterprise software will become more open for customers and partners to build custom apps. We’re already seeing the migration from monolithic software stacks to microservices that help to isolate and compartmentalize software development. Breaking apart code in this manner allows small dedicated teams to focus exclusively on specific areas with minimal impact on the whole. This trend will continue in 2019, and we’ll see organizations preparing their technology infrastructures for this approach to enterprise software adoption, to negate the need for massive customization projects.

Edge Computing will change how we process data. We’ll see a higher degree of computing happening at initial data capture to remove processing workload from the server side. This is essentially what’s already happening with IoT; however, in the future, we’ll see this in other non-IoT uses cases as well, like ensuring financial compliance locally instead of in a central data center. Edge computing takes advantage of microservices architectures where chunks of application functionality can be sent to edge devices. This expands computing power indefinitely and is an exciting trend to watch in 2019.

Looking Beyond 2019

While I mentioned that chatbots may have been mostly hyped in 2018, they will find their usefulness in the coming years. I leave you with a final prediction for the future of chatbots and AI:

As the AI market matures, chatbot consolidation will begin. Everyone and their mother’s company is building chatbots, and there simply isn’t enough room for them all. Consumers won’t want to ask one chatbot how many PTO days they have left, call up another to find out their current credit card balance, and talk to a third to book a flight to Europe. Having a different chatbot for everything under the sun isn’t good UX. While we may not see this for another few years, as the market matures, chatbot consolidation will begin. The code needed for a chatbot to perform its dedicated task on the backend will still be valuable — chatbots will instead be recorded as the go-between with a customer-facing chatbot and the enabling backend software. This means the user will ask Cortana (for example) to perform a task, Cortana will ask the bot, the bot will perform the task, and Cortana will inform the user that the task is complete. Chatbots that perform useful and unique tasks won’t disappear, they’ll just become part of a larger ecosystem that’s one step removed from the consumer, where they interface with other solutions such as banks, airlines, ERP software, pizza parlors — literally everything.